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No-boundary thinking in bioinformatics research

Overview of attention for article published in BioData Mining, November 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

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20 X users

Citations

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11 Dimensions

Readers on

mendeley
63 Mendeley
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3 CiteULike
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Title
No-boundary thinking in bioinformatics research
Published in
BioData Mining, November 2013
DOI 10.1186/1756-0381-6-19
Pubmed ID
Authors

Xiuzhen Huang, Barry Bruce, Alison Buchan, Clare Bates Congdon, Carole L Cramer, Steven F Jennings, Hongmei Jiang, Zenglu Li, Gail McClure, Rick McMullen, Jason H Moore, Bindu Nanduri, Joan Peckham, Andy Perkins, Shawn W Polson, Bhanu Rekepalli, Saeed Salem, Jennifer Specker, Donald Wunsch, Donghai Xiong, Shuzhong Zhang, Zhongming Zhao

Abstract

Currently there are definitions from many agencies and research societies defining "bioinformatics" as deriving knowledge from computational analysis of large volumes of biological and biomedical data. Should this be the bioinformatics research focus? We will discuss this issue in this review article. We would like to promote the idea of supporting human-infrastructure (HI) with no-boundary thinking (NT) in bioinformatics (HINT).

X Demographics

X Demographics

The data shown below were collected from the profiles of 20 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 8%
United Kingdom 1 2%
Indonesia 1 2%
Unknown 56 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 21%
Researcher 13 21%
Other 6 10%
Professor > Associate Professor 6 10%
Professor 5 8%
Other 17 27%
Unknown 3 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 24%
Biochemistry, Genetics and Molecular Biology 9 14%
Computer Science 9 14%
Medicine and Dentistry 7 11%
Engineering 4 6%
Other 13 21%
Unknown 6 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 January 2021.
All research outputs
#3,088,276
of 26,179,695 outputs
Outputs from BioData Mining
#53
of 327 outputs
Outputs of similar age
#27,420
of 230,549 outputs
Outputs of similar age from BioData Mining
#2
of 8 outputs
Altmetric has tracked 26,179,695 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 327 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one has done well, scoring higher than 83% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 230,549 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.